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DATAMINE
2006
230views more  DATAMINE 2006»
13 years 7 months ago
Mining top-K frequent itemsets from data streams
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Raymond Chi-Wing Wong, Ada Wai-Chee Fu
IEAAIE
2009
Springer
14 years 2 months ago
An Efficient Algorithm for Maintaining Frequent Closed Itemsets over Data Stream
Data mining refers to the process of revealing unknown and potentially useful information from a large database. Frequent itemsets mining is one of the foundational problems in dat...
Show-Jane Yen, Yue-Shi Lee, Cheng-Wei Wu, Chin-Lin...
JIIS
2007
150views more  JIIS 2007»
13 years 7 months ago
Towards a new approach for mining frequent itemsets on data stream
Mining frequent patterns on streaming data is a new challenging problem for the data mining community since data arrives sequentially in the form of continuous rapid streams. In t...
Chedy Raïssi, Pascal Poncelet, Maguelonne Tei...
ICDE
2008
IEEE
192views Database» more  ICDE 2008»
14 years 9 months ago
Verifying and Mining Frequent Patterns from Large Windows over Data Streams
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
Barzan Mozafari, Hetal Thakkar, Carlo Zaniolo
KAIS
2008
150views more  KAIS 2008»
13 years 7 months ago
A survey on algorithms for mining frequent itemsets over data streams
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
James Cheng, Yiping Ke, Wilfred Ng